This book provides an overview of behavioral decision theory and related research findings. In brief, behavioral decision theory is a general term for descriptive theories to explain the psychological knowledge related to decision-making behavior. It is called a theory, but actually it is a combination of various psychological theories, for which no axiomatic systems, such as the utility theory widely used in economics, have been established; it is often limited to qualitative knowledge. However, as suggested in the studies of H. (...) A. Simon, who won the Nobel Prize for Economics in 1978, and D. Kahneman, who won the prize in 2002, the psychological methodology and knowledge of behavioral decision theory have been applied widely in such fields as economics, business administration, and engineering, and are expected to become more useful in the future. This book explains various behavioral decision theories related to decision-making processes. Numerous models have been proposed to explain the psychological processes related to such a selection of decision strategies, and this book also introduces some new models that are useful to explain decision-making processes. The book concludes with speculation about the future of modern behavioral decision theories while referring to their relation to fields associated with neuroscience, such as neuroeconomics, that have been developed in recent years. In addition, each chapter includes a bibliography that can be referred to when studying more details related to behavioral decision theory. Reading this book requires no advanced expertise; nonetheless, an introductory knowledge of psychology, business administration, and economics, and approximately a high school graduate’s level of mathematics should facilitate the reader’s comprehension of the content. (shrink)

A selection of 15 papers on choice modeling are presented in this volume.

This book presents a comprehensive review of the emerging theories from cognitive science that integrate both decision processes and choice behavior.

This study examined individual differences in mathematics learning by combining antecedent (A), opportunity (O), and propensity (P) indicators within the Opportunity-Propensity model. Although there is already some evidence for this model based on secondary datasets, there currently is no primary data available that simultaneously takes into account A,O and P factors in children with and without Mathematical Learning Disabilities (MLD). Therefore the mathematical abilities of 114 school-aged children (grade 3 till 6) with and without MLD were analyzed and (...) combined with information retrieved from standardized tests and questionnaires. Results indicated significant differences in personality, motivation, temperament, subjective well-being, self-esteem, self-perceived competence and parental aspirations when comparing children with and without MLD. In addition, A, O and P factors were found to underlie mathematical abilities and disabilities. For the A factors, parental aspirations explained about half of the variance in fact retrieval speed in children without MLD, and SES was especially involved in the prediction of procedural accuracy in general. Teachers’ experience contributed as O factor and explained about 6% of the variance in mathematical abilities. P indicators explained between 52 and 69% of the variance, with especially intelligence as overall significant predictor. Indirect effects pointed towards the interrelatedness of the predictors and the value of including A, O and P indicators in a comprehensive model. The role parental aspirations played in fact retrieval speed was partially mediated through the self-perceived competence of the children, whereas the effect of SES on procedural accuracy was partially mediated through intelligence in children of both groups and through working memory capacity in children with MLD. Moreover, in line with the componential structure of mathematics, our findings were dependent on the math task used. Different A, O and P indicators seemed to be important for fact retrieval speed compared to procedural accuracy. Also, mathematical development type (MLD or typical development) mattered since some A, O and P factors were predictive for MLD only and the other way around. Practical implications of these findings and recommendations for future research on MLD and on individual differences in mathematical abilities are provided. (shrink)

Over the last decade, fully distributed models have become dominant in connectionist psychological modelling, whereas the virtues of localist models have been underestimated. This target article illustrates some of the benefits of localist modelling. Localist models are characterized by the presence of localist representations rather than the absence of distributed representations. A generalized localist model is proposed that exhibits many of the properties of fully distributed models. It can be applied to a number of problems that (...) are difficult for fully distributed models, and its applicability can be extended through comparisons with a number of classic mathematical models of behaviour. There are reasons why localist models have been underused, though these often misconstrue the localist position. In particular, many conclusions about connectionist representation, based on neuroscientific observation, can be called into question. There are still some problems inherent in the application of fully distributed systems and some inadequacies in proposed solutions to these problems. In the domain of psychological modelling, localist modelling is to be preferred. Key Words: choice; competition; connectionist modelling; consolidation; distributed; localist; neural networks; reaction-time. (shrink)

We investigate the mathematics of a model of the human mind which has been proposed by the psychologist Jens Mammen. Mathematical realizations of this model consists of what the first author (A.T.) has called Mammen spaces, where a Mammen space is a triple in the Baumgartner–Laver model.Finally, consequences for psychology are discussed.

This book offers a rigorous, concise, and nontechnical introduction to some of the fundamental insights of rational choice theory. It draws on formal theories of microeconomics, decision making, games, and social choice, and on ideas developed in philosophy, psychology, and sociology. Itzhak Gilboa argues that economic theory has provided a set of powerful models and broad insights that have changed the way we think about everyday life. He focuses on basic insights of the rational choice (...) paradigm--the general conceptualization rather than a particular theory--that survive recent critiques of economic theory's various failures. Gilboa explains the main concepts in language accessible to the nonspecialist, offering a nonmathematical guide to some of the main ideas developed in economic theory in the second half of the twentieth century. Chapters cover feasibility and desirability, utility maximization, constrained optimization, expected utility, probability and statistics, aggregation of preferences, games and equilibria, free markets, and rationality and emotions. Online appendixes offer additional material, including a survey of relevant mathematical concepts. (shrink)

The underrepresentation of females in mathematics-related fields may be explained by gender differences in mathematics self-concept (rather than ability) favoring males. Mathematics self-concept typically declines with student age, differs with student ethnicity, and is sensitive to teacher influence in early schooling. We investigated whether change in mathematics self-concept occurred within the context of a longitudinal intervention to raise and sustain teacher expectations of student achievement. This experimental study was conducted with a large sample of New Zealand primary school students and (...) their teachers. Data were analyzed using longitudinal multilevel modelling with mathematics self-concept as the dependent variable and time (which represents students’ increasing age each year), gender, and ethnicity entered as predictors and achievement in mathematics included as a control variable. Interaction terms were also explored to investigate changes over time for different groups. All students demonstrated a small increase in mathematics self-concept over the three-year period of the current study but mathematics self-concept was consistently greater for boys than girls. Māori, Asian, and Other students’ initial mathematics self-concept was higher than that of New Zealand European and Pacific Islanders’ (after controlling for achievement differences). However, a statistically significant decline in mathematics self-concept occurred for Māori students alone by the end of the study. The expected age-related reduction over time in student mathematics self-concept appeared to be mitigated in association with the longitudinal study. Nevertheless, the demonstration of a comparatively lower mathematics self-concept remained for girls overall and declined for Māori. Our results reinforce implications for future research into mathematics self-concept as a possible determinant of female student career choices. (shrink)

Models of intertemporal choice draw on three evaluation rules, which we compare in the restricted domain of choices between smaller sooner and larger later monetary outcomes. The hyperbolic discounting model proposes an alternative-based rule, in which options are evaluated separately. The interval discounting model proposes a hybrid rule, in which the outcomes are evaluated separately, but the delays to those outcomes are evaluated in comparison with one another. The tradeoff model proposes an attribute-based rule, in which both outcomes (...) and delays are evaluated in comparison with one another: People consider both the intervals between the outcomes and the compensations received or paid over those intervals. We compare highly general parametric functional forms of these models by means of a Bayesian analysis, a method of analysis not previously used in intertemporal choice. We find that the hyperbolic discounting model is outperformed by the interval discounting model, which, in turn, is outperformed by the tradeoff model. Our cognitive modeling is among the first to offer quantitative evidence against the conventional view that people make intertemporal choices by discounting the value of future outcomes, and in favor of the view that they directly compare options along the time and outcome attributes. (shrink)

We examined how children’s strategy choices in solving complex subtraction problems are related to grade and to variations in problem complexity. In two studies, third- and fifth-grade children (N≈160 each study) solved multi-digit subtraction problems (e.g., 34 - 18) and described their solution strategies. In the first experiment, strategy selection was investigated by means of a free-choice paradigm, whereas in the second study a discrete-choice approach was implemented. In both experiments, analyses of strategy repertoire indicated that third-grade children (...) were more likely to report less-efficient strategies (i.e., counting) and relied more on the right-to-left solution algorithm compared to fifth-grade children who more often used efficient memory-based retrieval and conceptually-based left-to-right (i.e., decomposition) strategies. Nevertheless, all strategies were reported or selected by both older and younger children and strategy use varied with problem complexity and presentation format for both age groups. These results supported the overlapping waves model of strategy development and provide detailed information about patterns of strategy choice on complex subtraction problems. (shrink)

Individuals make decisions under uncertainty every day. Decisions are based on in- complete information concerning the potential outcome or the predicted likelihood with which events occur. In addition, individuals’ choices often deviate from the rational or mathematically objective solution. Accordingly, the dynamics of human decision making are difficult to capture using conventional, linear mathematical models. Here, we present data from a 2-choice task with variable risk between sure loss and risky loss to illustrate how a simple nonlinear (...) dynamical system can be employed to capture the dynamics of human decision making under uncertainty (i.e., multistability, bifurcations). We test the feasibility of this model quantitatively and demonstrate how the model can account for up to 86% of the observed choice behavior. The implications of using dynamical models for explaining the nonlin- ear complexities of human decision making are discussed as well as the degree to which the theory of nonlinear dynamical systems might offer an alternative framework for understanding human decision making processes. (shrink)

In experiments of games, players frequently make choices which are regarded as irrational in game theory. In papers of Khrennikov (Information Dynamics in Cognitive, Psychological and Anomalous Phenomena. Fundamental Theories of Physics, Kluwer Academic, Norwell, 2004; Fuzzy Sets Syst. 155:4–17, 2005; Biosystems 84:225–241, 2006; Found. Phys. 35(10):1655–1693, 2005; in QP-PQ Quantum Probability and White Noise Analysis, vol. XXIV, pp. 105–117, 2009), it was pointed out that statistics collected in such the experiments have “quantum-like” properties, which can not be explained in (...) classical probability theory. In this paper, we design a simple quantum-like model describing a decision-making process in a two-players game and try to explain a mechanism of the irrational behavior of players. Finally we discuss a mathematical frame of non-Kolmogorovian system in terms of liftings (Accardi and Ohya, in Appl. Math. Optim. 39:33–59, 1999). (shrink)

Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty (...) and the reduction thereof. However, a variety of alternative entropy metrics (Hartley, Quadratic, Tsallis, Rényi, and more) are popular in the social and the natural sciences, computer science, and philosophy of science. Particular entropy measures have been predominant in particular research areas, and it is often an open issue whether these divergences emerge from different theoretical and practical goals or are merely due to historical accident. Cutting across disciplinary boundaries, we show that several entropy and entropy reduction measures arise as special cases in a unified formalism, the Sharma–Mittal framework. Using mathematical results, computer simulations, and analyses of published behavioral data, we discuss four key questions: How do various entropy models relate to each other? What insights can be obtained by considering diverse entropy models within a unified framework? What is the psychological plausibility of different entropy models? What new questions and insights for research on human information acquisition follow? Our work provides several new pathways for theoretical and empirical research, reconciling apparently conflicting approaches and empirical findings within a comprehensive and unified information-theoretic formalism. (shrink)

A conceptual and mathematical model of a social community behavior in a choice situation under a veil of ignorance, where two alternative policies—Rawlsian maximin and Harsanyian utilitarianism—can be implemented through the aggregation of individual preferences over these two policies, is constructed and investigated. We first incorporate in our conceptual model psychological features such as risk-aversion and prosocial preferences that likely underlie choices of welfare policies. We secondly develop and select the mathematical model presented it by means of (...) an autonomous system of ordinary differential equations. A qualitative analysis of this system global phase-plane behavior shows possible tendencies of community development under social choices over Rawlsian or utilitarian societies depending on psychological parameters such as risk aversion and prosocial preferences. (shrink)

This book contributes to the developing dialogue between cognitive science and social sciences. It focuses on a central issue in both fields, i.e. the nature and the limitations of the rationality of beliefs and action. The development of cognitive science is one of the most important and fascinating intellectual advances of recent decades, and social scientists are paying increasing attention to the findings of this new branch of science that forces us to consider many classical issues related to epistemology and (...) philosophy of action in a new light. This book encourages scholars from different fields who are interested in the dialogue between cognitive science and social sciences, to develop and analyze new perspectives that allow us to elucidate the mystery of rationality. What is rationality? What are its limitations? What rationality assumptions must be used to study social and economic phenomena? The target audience primarily comprises researchers and experts in the field. Analysis of the concept of rationality is a leitmotiv in the history of the social sciences and has involved endless disputes. Since it is difficult to give a precise definition of this concept, and there is a lack of agreement about its meaning, it is possible to say that there is a ‘mystery of rationality’. What is it to be rational? Is rationality merely instrumental or does it also involve the endorsement of values, i.e. the choice of goals? Should we consider rationality to be a normative principle or a descriptive one? Can rationality be only Cartesian or can it also be argumentative? Is rationality a conscious skill or a partly tacit one? This book, which has been written by an outstanding collection of authors, including both philosophers and social scientists, tries to make a useful contribution to the debates on these problems and shed some light on the mystery of rationality. (shrink)

Rational addiction theories illustrate how absurd choice theories in economics get taken seriously as possibly true explanations and tools for welfare analysis despite being poorly interpreted, empirically unfalsifiable, and based on wildly inaccurate assumptions selectively justified by ad-hoc stories. The lack of transparency introduced by poorly anchored mathematical models, the psychological persuasiveness of stories, and the way the profession neglects relevant issues are suggested as explanations for how what we perhaps should see as displays of technical skill (...) and ingenuity are allowed to blur the lines between science and games. (shrink)

Among the main concerns of 20th century philosophy was that of the foundations of mathematics. But usually not recognized is the relevance of the choice of a foundational approach to the other main problems of 20th century philosophy, i.e., the logical structure of language, the nature of scientific theories, and the architecture of the mind. The tools used to deal with the difficulties inherent in such problems have largely relied on set theory and its “received view”. There are specific (...) issues, in philosophy of language, epistemology and philosophy of mind, where this dependence turns out to be misleading. The same issues suggest the gain in understanding coming from category theory, which is, therefore, more than just the source of a “non-standard” approach to the foundations of mathematics. But, even so conceived, it is the very notion of what a foundation has to be that is called into question. The philosophical meaning of mathematics is no longer confined to which first principles are assumed and which “ontological” interpretation is given to them in terms of some possibly updated version of logicism, formalism or intuitionism. What is central to any foundational project proper is the role of universal constructions that serve to unify the different branches of mathematics, as already made clear in 1969 by Lawvere. Such universal constructions are best expressed by means of adjoint functors and representability up to isomorphism. In this lies the relevance of a category-theoretic perspective, which leads to wide-ranging consequences. One such is the presence of functorial constraints on the syntax–semantics relationships; another is an intrinsic view of (constructive) logic, as arises in topoi and, subsequently, in more general fibrations. But as soon as theories and their models are described accordingly, a new look at the main problems of 20th century’s philosophy becomes possible. The lack of any satisfactory solution to these problems in a purely logical and set-theoretic setting is the result of too circumscribed an approach, such as a static and punctiform view of objects and their elements, and a misconception of geometry and its historical changes before, during, and after the foundational “crisis”, as if algebraic geometry and synthetic differential geometry – not to mention algebraic topology – were secondary sources for what concerns foundational issues. The objectivity of basic geometrical intuitions also acts against the recent version of structuralism proposed as ‘the’ philosophy of category theory. On the other hand, the need for a consistent and adequate conceptual framework in facing the difficulties met by pre-categorical theories of language and scientific knowledge not only provides the basic concepts of category theory with specific applications but also suggests further directions for their development (e.g., in approaching the foundations of physics or the mathematical models in the cognitive sciences). This ‘virtuous’ circle is by now largely admitted in theoretical computer science; the time is ripe to realise that the same holds for classical topics of philosophy. (shrink)

Psychological empirical research has shown that human choice behavior often violates the assumptions of classical rational choice models. In the last few decades a new research field has emerged which aims to account for the observed choice behavior by resorting to the concepts and mathematical techniques developed in the realm of quantum physics, such as the “mental state vector” defined in a Hilbert space and the interference of quantum probability. This article is a short introduction (...) to the quantum-like approach to the description of cognitive processes. I argue that the mathematical apparatus of quantum physics can account for the observed violations of classical logic and can help develop effective models of psychological and cognitive phenomena. This is illustrated through the so-called conjunction and disjunction fallacies by providing an alternative interpretation of the results of Linda test and Hawaii test. No-fallacy configurations are made possible in the quantum-like approach by sequential modeling of mental states transitions. (shrink)

Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networkscharts the immense progress made in recent years in many specific areas related to two great questions: How does the brain work? and How can we build intelligent machines? While many books have appeared on limited aspects of one subfield or another of brain theory and neural networks, (...) the Handbookcovers the entire sweep of topics—from detailed models of single neurons, analyses of a wide variety of biological neural networks, and connectionist studies of psychology and language, to mathematical analyses of a variety of abstract neural networks, and technological applications of adaptive, artificial neural networks. The excitement, and the frustration, of these topics is that they span such a broad range of disciplines including mathematics, statistical physics and chemistry, neurology and neurobiology, and computer science and electrical engineering as well as cognitive psychology, artificial intelligence, and philosophy. Thus, much effort has gone into making the Handbookaccessible to readers with varied backgrounds while still providing a clear view of much of the recent, specialized research in specific topics. The heart of the book, part III, comprises of 267 original articles by leaders in the various fields, arranged alphabetically by title. Parts I and II, written by the editor, are designed to help readers orient themselves to this vast range of material. Part I, Background, introduces several basic neural models, explains how the present study of brain theory and neural networks integrates brain theory, artificial intelligence, and cognitive psychology, and provides a tutorial on the concepts essential for understanding neural networks as dynamic, adaptive systems. Part II, Road Maps, provides entry into the many articles of part III through an introductory "Meta-Map" and twenty-three road maps, each of which tours all the Part III articles on the chosen theme. (shrink)

Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networks charts the immense progress made in recent years in many specific areas related to great questions: How does the brain work? How can we build intelligent machines? While many books discuss limited aspects of one subfield or another of brain theory and neural networks, the Handbook covers (...) the entire sweep of topics—from detailed models of single neurons, analyses of a wide variety of biological neural networks, and connectionist studies of psychology and language, to mathematical analyses of a variety of abstract neural networks, and technological applications of adaptive, artificial neural networks. Expository material makes the book accessible to readers with varied backgrounds while still offering a clear view of the recent, specialized research on specific topics. (shrink)

A predictive model applicable in both neurophysiological and decision-making studies is proposed, bridging the gap between psychological/behavioral and neurophysiological studies. Supposing the electromagnetic waves are carriers of decision-making, and electromagnetic waves with the same frequency, individual amplitude and constant phase triggered by conditions interfere with each other and the resultant intensity determines the probability of the decision. Accordingly, brainwave-interference decision-making model is built mathematically and empirically test with neurophysiological and behavioral data. Event-related potential data confirmed the stability of the phase (...) differences in a given decision context. Behavioral data analysis shows that phase stability exists across categorization-decision, two-stage gambling, and prisoner’s dilemma decisions. Irrational decisions occurring in those experiments are actually rational as their phases could be quantitatively derived from the phases of the riskiest and safest choices. Model fitting result reveals that the root-mean-square deviations between the fitted and actual phases of irrational decisions are less than 10°, and the mean absolute percentage errors of the fitted probabilities are less than 0.06. The proposed model is similar in mathematical form compared with the quantum modeling approach, but endowed with physiological/psychological connection and predictive ability, and promising in the integration of neurophysiological and behavioral research to explore the origin of the decision. (shrink)

Experimental research by social and cognitive psychologists has established that cooperative groups solve a wide range of problems better than individuals. Cooperative problem solving groups of scientific researchers, auditors, financial analysts, air crash investigators, and forensic art experts are increasingly important in our complex and interdependent society. This comprehensive textbook--the first of its kind in decades--presents important theories and experimental research about group problem solving. The book focuses on tasks that have demonstrably correct solutions within mathematical, logical, scientific, or (...) verbal systems, including algebra problems, analogies, vocabulary, and logical reasoning problems.The book explores basic concepts in group problem solving, social combination models, group memory, group ability and world knowledge tasks, rule induction problems, letters-to-numbers problems, evidence for positive group-to-individual transfer, and social choice theory. The conclusion proposes ten generalizations that are supported by the theory and research on group problem solving. Group Problem Solving is an essential resource for decision-making research in social and cognitive psychology, but also extremely relevant to multidisciplinary and multicultural problem-solving teams in organizational behavior, business administration, management, and behavioral economics. (shrink)

Metalogic is an open-ended cognitive, formal methodology pertaining to semantics and information processing. The language that mathematizes metalogic is known as metalanguage and deals with metafunctions purely by extension on patterns. A metalogical process involves an effective enrichment in knowledge as logical statements, and, since human cognition is an inherently logic–based representation of knowledge, a metalogical process will always be aimed at developing the scope of cognition by exploring possible cognitive implications reflected on successive levels of abstraction. Indeed, it is (...) basically impracticable to maintain logic–and–metalogic without paying heed to cognitive theorizing. For it is cognitively irrelevant whether possible conclusions are deduced from some premises before the premises are determined to be true or whether the premises themselves are determined to be true first and, then, the conclusions are deduced from them. In this paper we consider the term metalogic as inherently embodied under the framework referred to as cognitive science and mathematics. We propose a metalogical interpretation of Arrow’s impossibility theorem and, to that end, choice theory is understood as a mental course of action dealing with logic and metalogic issues, in which a possible mathematical approach to model a mental course of action is adopted as a systematic operating method. Nevertheless, if we look closely at the core of Arrow’s impossibility theorem in terms of metalogic, a second fundamental contribution to this framework is represented by the Nash equilibrium. As a result of the foregoing, therefore, we prove the metalogical equivalence between Arrow’s impossibility theorem and the existence of the Nash equilibrium. More specifically, Arrow’s requirements correspond to the Nash equilibrium for finite mixed strategies with no symmetry conditions. To demonstrate this proof, we first verify that Arrow’s set and Nash’s set are isomorphic to each other, both sets being under stated conditions of non–symmetry. Then, the proof is completed by virtue of category theory. Indeed, the two sets are categories that correspond biuniquely to one another and, thus, it is possible to define a covariant functor that preserves their mutual structures. According to this, we show the proof–dedicated metalanguage as a precursor to a special equivalence theorem. (shrink)

While the paradigm of utility maximisation has formed the basis of the majority of applications in discrete choice modelling for over 40 years, its core assumptions have been questioned by work in both behavioural economics and mathematical psychology as well as more recently by developments in the RUM-oriented choice modelling community. This paper reviews the basic properties with a view to explaining the historical pre-eminence of utility maximisation and addresses the question of what departures from the (...) paradigm may be necessary or wise in order to accommodate richer behavioural patterns. We find that many, though not all, of the behavioural traits discussed in the literature can be approximated sufficiently closely by a random utility framework, allowing analysts to retain the many advantages that such an approach possesses. (shrink)

This book is not what one might expect from either the title or the author. It is not about the sociological or philosophical doctrines which are associated with the title, and although Piaget's long work in human development is the basis for the views of this book, it is not the subject matter. The book is a reflective essay on structuralism as a method, and a call for a comprehensive science of man using that method. Traditionally, "Structuralism" had both positive (...) and negative meanings: positively it stood for the ideal of intelligibility; as a critical position it is allied with specific oppositions to a wide variety of atomisms and compartmentalizations. Piaget's characterization of "Structuralism" is deliberately broad, in order to capture the notion common to linguistic structuralism, Gestalt psychology, and the concepts of structures employed by logic, mathematics, physics, biology, and the social sciences. Minimally, a structure is a totality involving a system of laws for transformations; it is self-regulating, preserving and enriching itself through the exercise of its transformations without losing its unity or appealing to external elements. A living organism, the prototype of a structure, is simultaneously one physico-chemical system among others, and the source of its own activities. A structure can be formalized, and is adaptable to models of various sorts, logico-mathematical, cybernetic, etc., but it is independent of the theoretician's choice of the formal system in which it is expressed. When we can reduce a field of knowledge to a formalization of a self-regulating structure we will feel we are nearing the inner motive force of the system; this is what is important about structuralism, and what raises our hopes. But we are not nearly at that point. An authentic biologically-based structuralism is only beginning to take shape after centuries of either a simplifying reductionism or a vitalism more verbal than really explanatory. Piaget tells us that the comprehensive science of man which we need, based on structuralist ideals, and not recognizing separated disciplines, can only be achieved via thoroughgoing structuralist method.--M. B. M. (shrink)